FACSresponseBFP
Edwin Eliasson
10/14/2021
Load libraries
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## ✓ tidyr 1.1.3 ✓ stringr 1.4.0
## ✓ readr 2.0.1 ✓ forcats 0.5.1## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
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## transpose#setwd("../Induction_system/Facs/Data analysis/Script")Load data
#All data is in csv format in the “../data/2021-08-27_at_08-43-55am” folder
filenames = list.files(path = "../data/FACS_2021_09_09_CSV/Sample Group - 1 - Gate A/",full.names = T)
# Extract plate position from filename
sample_name = filenames %>% gsub("_Data Source - 1_A.csv","",.) %>% gsub("le_Group_1_","",.) %>% gsub(".*am.","",.)
# Loop through and merge all files into a big tibble
tbl = tibble()
for (i in 1:length(filenames)) {
tbl_file = fread(filenames[i]) %>% mutate(POS = sample_name[i])
tbl = rbind(tbl,tbl_file)
}
rm(tbl_file)#Extraion of compensated data
filenames_comp = list.files(path = "../data/FACS_2021_09_09_CSV/Compensation Panel/",full.names = T)
# Extract plate position from filename
sample_name_comp = filenames_comp %>% gsub("_Data Source - 1_A.csv","",.) %>% gsub("le_Group_1_Compensation Panel_","",.) %>% gsub("EGFP_EGFP_A.csv","pGFP",.) %>% gsub("miRFP670_miRFP670_A.csv","pRFP",.) %>% gsub("Pacific Blue_Pacific Blue_A.csv","pBFP",.) %>% gsub("Negative Control_Negative Control_A.csv","pCENPK",.) %>% gsub(".*am.","",.)
# Loop through and merge all files from compensated into a big tibble
tbl_comp = tibble()
for (i in 1:length(filenames_comp)) {
tbl_file_comp = fread(filenames_comp[i]) %>% mutate(POS = sample_name_comp[i])
tbl_comp = rbind(tbl_comp,tbl_file_comp)
}
rm(tbl_file_comp)Pre-procesing
#Replacement of hypgen (-) in columns & removal of defected index column
names(tbl) <- gsub("\\-",".", names(tbl))
names(tbl) <- gsub("\\.A.Compensated","", names(tbl))
names(tbl) <- gsub("\\Pacific Blue","BFP", names(tbl))
tbl$Index = NULL
glimpse(tbl)## Rows: 805,085
## Columns: 9
## $ TIME <dbl> 0.0000000000, 0.0006514286, 0.0008228571, 0.0013028570, 0.002…
## $ FSC.A <dbl> 412479.8, 451923.9, 413993.8, 335756.6, 413562.6, 403134.8, 2…
## $ FSC.H <dbl> 286600.2, 311926.7, 318567.2, 241114.7, 282876.2, 246048.3, 1…
## $ FSC.W <int> 315, 314, 303, 288, 310, 319, 243, 277, 254, 290, 325, 272, 3…
## $ BSC.A <dbl> 416602.2, 406967.0, 391401.6, 236016.6, 400477.4, 489543.5, 1…
## $ BFP <dbl> -252.0389000, -797.4771000, -495.7184000, -13.1588000, -321.6…
## $ EGFP <dbl> 569.9741, 394.6888, 271.0912, 170.9802, 389.3646, 672.5525, 4…
## $ miRFP670 <dbl> 9259.660, 17388.250, 11075.980, 4165.408, 9231.049, 27801.610…
## $ POS <chr> "Cup_500", "Cup_500", "Cup_500", "Cup_500", "Cup_500", "Cup_5…#Hypen replacemnt and name changing
names(tbl_comp) <- gsub("\\-",".", names(tbl_comp))
names(tbl_comp) <- gsub("\\Pacific Blue.A","BFP", names(tbl_comp))
names(tbl_comp) <- gsub("\\EGFP.A","EGFP", names(tbl_comp))
names(tbl_comp) <- gsub("\\miRFP670.A","miRFP670", names(tbl_comp))
head(tbl_comp)## TIME FSC.A FSC.H BSC.A BSC.H BFP Pacific Blue.H
## 1: 0.0000000000 250295.5 226971.4 185710.7 149791.0 623.97500 1406.72
## 2: 0.0003885714 396567.4 281930.9 333183.9 190849.1 926.52400 1535.52
## 3: 0.0053828570 298409.3 222418.6 270935.5 184513.3 705.49300 1305.92
## 4: 0.0057600000 259285.1 223678.6 196818.6 135167.2 -16.21263 1230.88
## 5: 0.0067771430 175036.8 136286.1 205532.6 142713.8 349.11840 1118.88
## 6: 0.0068914280 407149.9 284247.0 335362.9 183232.0 352.24830 1604.96
## EGFP EGFP.H miRFP670 miRFP670.H POS
## 1: 180.8407 377.44 192.91620 439.04 pGFP
## 2: 335.5266 362.88 129.08370 301.28 pGFP
## 3: 471.2275 445.76 163.96740 445.76 pGFP
## 4: 15331.7600 15573.60 293.43010 730.24 pGFP
## 5: 379.7134 469.28 375.61960 395.36 pGFP
## 6: 330.7506 572.32 66.79992 266.56 pGFPFilter out cells with negative intensity and log transform
tbl =
tbl %>%
filter(EGFP > 0) %>%
mutate(log_EGFP = log10(EGFP+1)) %>%
filter(miRFP670 > 0) %>%
mutate(log_miRFP670 = log10(miRFP670+1)) %>%
filter(BFP > 0) %>%
mutate(log_BFP = log10(BFP+1))
head(tbl)## TIME FSC.A FSC.H FSC.W BSC.A BFP EGFP miRFP670
## 1: 0.004114286 301259.0 223201.4 277 283638.4 265.6477000 240.9676 1302.427
## 2: 0.005257143 283938.8 268095.5 254 166749.9 78.7960400 270.1115 2841.754
## 3: 0.007451429 279311.8 224771.7 265 237945.1 0.7901272 193.7543 6821.914
## 4: 0.014422860 343853.7 228942.6 293 332054.0 37.0436700 585.3580 3921.094
## 5: 0.015554290 318554.7 280707.8 265 242094.0 111.2441000 304.3398 2294.979
## 6: 0.017085710 260285.7 203609.3 261 196030.8 202.8584000 196.0150 4978.650
## POS log_EGFP log_miRFP670 log_BFP
## 1: Cup_500 2.383757 3.115087 2.4259378
## 2: Cup_500 2.433148 3.453739 1.9019813
## 3: Cup_500 2.289487 3.833970 0.2528839
## 4: Cup_500 2.768163 3.593518 1.5802824
## 5: Cup_500 2.484783 3.360968 2.0501635
## 6: Cup_500 2.294499 3.697199 2.3093286Filter out cells with negative intensity and log transform ofr comp
tbl_comp =
tbl_comp %>%
filter(EGFP > 0) %>%
mutate(log_EGFP = log10(EGFP+1)) %>%
filter(miRFP670 > 0) %>%
mutate(log_miRFP670 = log10(miRFP670+1)) %>%
filter(BFP > 0) %>%
mutate(log_BFP = log10(BFP+1))
head(tbl_comp)## TIME FSC.A FSC.H BSC.A BSC.H BFP Pacific Blue.H
## 1: 0.0000000000 250295.5 226971.4 185710.7 149791.0 623.9750 1406.72
## 2: 0.0003885714 396567.4 281930.9 333183.9 190849.1 926.5240 1535.52
## 3: 0.0053828570 298409.3 222418.6 270935.5 184513.3 705.4930 1305.92
## 4: 0.0067771430 175036.8 136286.1 205532.6 142713.8 349.1184 1118.88
## 5: 0.0068914280 407149.9 284247.0 335362.9 183232.0 352.2483 1604.96
## 6: 0.0070057140 403275.3 252297.9 448210.6 242881.0 766.9320 1845.76
## EGFP EGFP.H miRFP670 miRFP670.H POS log_EGFP log_miRFP670 log_BFP
## 1: 180.8407 377.44 192.91620 439.04 pGFP 2.259691 2.287614 2.795863
## 2: 335.5266 362.88 129.08370 301.28 pGFP 2.527019 2.114223 2.967325
## 3: 471.2275 445.76 163.96740 445.76 pGFP 2.674151 2.217398 2.849108
## 4: 379.7134 469.28 375.61960 395.36 pGFP 2.580598 2.575903 2.544215
## 5: 330.7506 572.32 66.79992 266.56 pGFP 2.520812 1.831229 2.548080
## 6: 359.2337 433.44 862.64830 760.48 pGFP 2.556584 2.936337 2.885323#Add index for cell
tbl <- tbl %>% mutate(cell_id = 1:nrow(tbl))
tbl_comp <- tbl_comp %>% mutate(cell_id = 1:nrow(tbl_comp))#Convert into tidy tibble and add channel info
tbl_tidy =
tbl %>%
pivot_longer(-c(POS,TIME,cell_id),names_to = "CHANNEL",values_to = "INTENSITY")
#mutate(SCALE = ifelse(grepl("Lin",CHANNEL),"lin","log")) %>%
glimpse(tbl_tidy)## Rows: 5,421,310
## Columns: 5
## $ TIME <dbl> 0.004114286, 0.004114286, 0.004114286, 0.004114286, 0.004114…
## $ POS <chr> "Cup_500", "Cup_500", "Cup_500", "Cup_500", "Cup_500", "Cup_…
## $ cell_id <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, …
## $ CHANNEL <chr> "FSC.A", "FSC.H", "FSC.W", "BSC.A", "BFP", "EGFP", "miRFP670…
## $ INTENSITY <dbl> 3.012590e+05, 2.232014e+05, 2.770000e+02, 2.836384e+05, 2.65…#Convert into tidy tibble and add channel info
tbl_tidy_comp =
tbl_comp %>%
pivot_longer(-c(POS,TIME,cell_id),names_to = "CHANNEL",values_to = "INTENSITY")
#mutate(SCALE = ifelse(grepl("Lin",CHANNEL),"lin","log")) %>%
glimpse(tbl_tidy_comp)## Rows: 1,164,605
## Columns: 5
## $ TIME <dbl> 0.0000000000, 0.0000000000, 0.0000000000, 0.0000000000, 0.00…
## $ POS <chr> "pGFP", "pGFP", "pGFP", "pGFP", "pGFP", "pGFP", "pGFP", "pGF…
## $ cell_id <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, …
## $ CHANNEL <chr> "FSC.A", "FSC.H", "BSC.A", "BSC.H", "BFP", "Pacific Blue.H",…
## $ INTENSITY <dbl> 2.502955e+05, 2.269714e+05, 1.857107e+05, 1.497910e+05, 6.23…#Format meta data
tbl_meta =
fread(file = "../data/plate_map.csv") %>%
mutate(DOSE = as.character(DOSE)) %>%
mutate(DOSE_1 = as.character(DOSE_1)) %>%
mutate(DOSE_2 = as.character(DOSE_2)) %>%
mutate(DOSE_3 = as.character(DOSE_3))#Format meta data
tbl_meta_comp =
fread(file = "../data/plate_map2.csv") %>%
mutate(DOSE = as.character(DOSE)) %>%
mutate(DOSE_1 = as.character(DOSE_1)) %>%
mutate(DOSE_2 = as.character(DOSE_2)) %>%
mutate(DOSE_3 = as.character(DOSE_3))#Merge meta data with FACS meta data
tbl_tidy =
tbl_tidy %>%
full_join(tbl_meta,by = "POS")
head(tbl_tidy)## # A tibble: 6 × 15
## TIME POS cell_id CHANNEL INTENSITY CASE_CTRL INDUCER_1 DOSE_1 INDUCER_2
## <dbl> <chr> <int> <chr> <dbl> <chr> <chr> <chr> <chr>
## 1 0.00411 Cup_500 1 FSC.A 301259 CASE CUP 500 none
## 2 0.00411 Cup_500 1 FSC.H 223201. CASE CUP 500 none
## 3 0.00411 Cup_500 1 FSC.W 277 CASE CUP 500 none
## 4 0.00411 Cup_500 1 BSC.A 283638. CASE CUP 500 none
## 5 0.00411 Cup_500 1 BFP 266. CASE CUP 500 none
## 6 0.00411 Cup_500 1 EGFP 241. CASE CUP 500 none
## # … with 6 more variables: DOSE_2 <chr>, INDUCER_3 <chr>, DOSE_3 <chr>,
## # STRAIN <chr>, DOSE <chr>, NUM.IND <int>#Merge meta data with FACS meta data
tbl_tidy_comp =
tbl_tidy_comp %>%
full_join(tbl_meta_comp,by = "POS")
head(tbl_tidy_comp)## # A tibble: 6 × 15
## TIME POS cell_id CHANNEL INTENSITY CASE_CTRL INDUCER_1 DOSE_1 INDUCER_2
## <dbl> <chr> <int> <chr> <dbl> <chr> <chr> <chr> <chr>
## 1 0 pGFP 1 FSC.A 250296. CTRL EST 0.01 none
## 2 0 pGFP 1 FSC.H 226971. CTRL EST 0.01 none
## 3 0 pGFP 1 BSC.A 185711. CTRL EST 0.01 none
## 4 0 pGFP 1 BSC.H 149791 CTRL EST 0.01 none
## 5 0 pGFP 1 BFP 624. CTRL EST 0.01 none
## 6 0 pGFP 1 Pacific Blue.H 1407. CTRL EST 0.01 none
## # … with 6 more variables: DOSE_2 <chr>, INDUCER_3 <chr>, DOSE_3 <chr>,
## # STRAIN <chr>, DOSE <chr>, NUM.IND <int>#Merge tbl and tbl_comp
tbl_tidy_merge =
tbl_tidy %>%
full_join(tbl_tidy_comp)## Joining, by = c("TIME", "POS", "cell_id", "CHANNEL", "INTENSITY", "CASE_CTRL", "INDUCER_1", "DOSE_1", "INDUCER_2", "DOSE_2", "INDUCER_3", "DOSE_3", "STRAIN", "DOSE", "NUM.IND")head(tbl_tidy_merge)## # A tibble: 6 × 15
## TIME POS cell_id CHANNEL INTENSITY CASE_CTRL INDUCER_1 DOSE_1 INDUCER_2
## <dbl> <chr> <int> <chr> <dbl> <chr> <chr> <chr> <chr>
## 1 0.00411 Cup_500 1 FSC.A 301259 CASE CUP 500 none
## 2 0.00411 Cup_500 1 FSC.H 223201. CASE CUP 500 none
## 3 0.00411 Cup_500 1 FSC.W 277 CASE CUP 500 none
## 4 0.00411 Cup_500 1 BSC.A 283638. CASE CUP 500 none
## 5 0.00411 Cup_500 1 BFP 266. CASE CUP 500 none
## 6 0.00411 Cup_500 1 EGFP 241. CASE CUP 500 none
## # … with 6 more variables: DOSE_2 <chr>, INDUCER_3 <chr>, DOSE_3 <chr>,
## # STRAIN <chr>, DOSE <chr>, NUM.IND <int>tbl_tidy = tbl_tidy_merge#Matrix with flipped columns
tbl_red_green_blue =
tbl_tidy %>%
filter(CHANNEL %in% c("log_EGFP", "log_miRFP670","log_BFP")) %>%
pivot_wider(names_from = CHANNEL, values_from = INTENSITY)
glimpse(tbl_red_green_blue)## Rows: 631,716
## Columns: 16
## $ TIME <dbl> 0.004114286, 0.005257143, 0.007451429, 0.014422860, 0.015…
## $ POS <chr> "Cup_500", "Cup_500", "Cup_500", "Cup_500", "Cup_500", "C…
## $ cell_id <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17…
## $ CASE_CTRL <chr> "CASE", "CASE", "CASE", "CASE", "CASE", "CASE", "CASE", "…
## $ INDUCER_1 <chr> "CUP", "CUP", "CUP", "CUP", "CUP", "CUP", "CUP", "CUP", "…
## $ DOSE_1 <chr> "500", "500", "500", "500", "500", "500", "500", "500", "…
## $ INDUCER_2 <chr> "none", "none", "none", "none", "none", "none", "none", "…
## $ DOSE_2 <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0…
## $ INDUCER_3 <chr> "none", "none", "none", "none", "none", "none", "none", "…
## $ DOSE_3 <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0…
## $ STRAIN <chr> "Cup", "Cup", "Cup", "Cup", "Cup", "Cup", "Cup", "Cup", "…
## $ DOSE <chr> "500", "500", "500", "500", "500", "500", "500", "500", "…
## $ NUM.IND <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
## $ log_EGFP <dbl> 2.383757, 2.433148, 2.289487, 2.768163, 2.484783, 2.29449…
## $ log_miRFP670 <dbl> 3.115087, 3.453739, 3.833970, 3.593518, 3.360968, 3.69719…
## $ log_BFP <dbl> 2.4259378, 1.9019813, 0.2528839, 1.5802824, 2.0501635, 2.…Single plasmid TETON
#TetON violin plot, log scale
p_violoin_tet_BFP =
tbl_tidy %>%
filter(STRAIN %in% c("Tet","CENPK")) %>%
filter(NUM.IND %in% c("1")) %>%
filter(CHANNEL %in% c("log_BFP")) %>%
ggplot(aes(x = DOSE_1,y = INTENSITY,group = DOSE_1, fill = DOSE_1)) +
geom_violin(alpha = 0.5, adjust = 0.0001,draw_quantiles = 0.5) +
facet_wrap(vars(CASE_CTRL),ncol = 10) +
scale_color_viridis(name = "DOSE (µM)",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM)", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
stat_compare_means(ref.group = "0",label = "p.signif", method = "wilcox.test") +
ggtitle("Violin plot of BFP - Tetracyclin plasmid") +
xlab("Tetracyclin (µM)") +
ylab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_violoin_tet_BFP## Warning: Computation failed in `stat_compare_means()`:
## argument "x" is missing, with no default## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
#BFP expression depending of Tetracyclin conc.
p_density_tet_BFP_diff_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet")) %>%
ggplot(aes(log_BFP, color = DOSE_1, fill = DOSE_1)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE_1, INDUCER_1),nrow = 2) +
scale_color_viridis(name = "DOSE (µM)",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM)",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression - Tetracyclin plasmid") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_tet_BFP_diff_plot
#RFP expression depending of Tetracyclin conc.in ONE plot
p_density_tet_BFP_same_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet")) %>%
ggplot(aes(log_BFP, color = DOSE_1, fill = DOSE_1)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
scale_color_viridis(name = "DOSE (µM)",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM)",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression - Tetracyclin plasmid") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_tet_BFP_same_plot
LINCOLN GFP expression depending of EST
p_density_tet_BFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet")) %>%
ggplot(lincoln_weather, mapping = aes(x = log_BFP, y = DOSE_1, fill = stat(x))) +
geom_density_ridges_gradient(scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Expression", option = "magma") +
theme_bw() +
ggtitle("Density plots for BFP expression - Tetracyclin plasmid") +
ylab("DOSE (µM)") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))
p_density_tet_BFP_lincoln## Picking joint bandwidth of 0.0883
Double plasmid Tetracycline & Estradiol
#BFP & GFP violin expression
p_violin_Tet.est_BFP_GFP =
tbl_tidy %>%
filter(STRAIN %in% c("Tet.Est")) %>%
filter(NUM.IND %in% c("2")) %>%
filter(CHANNEL %in% c("log_BFP","log_EGFP")) %>%
ggplot(aes(x = DOSE,y = INTENSITY,group = DOSE, fill = DOSE)) +
geom_violin(alpha = 0.5, adjust = 0.0001,draw_quantiles = 0.5) +
scale_color_viridis(name = "DOSE (µM),
Tet/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
stat_compare_means(ref.group = "0/0",label = "p.signif", method = "wilcox.test") +
ggtitle("Violin plot of BFP & GFP intensity -
Tetracyclin & Estradiol plasmids") +
facet_wrap(vars(CHANNEL, STRAIN)) +
xlab("Tetracyclin and Estradiol (µM)") +
ylab("Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_violin_Tet.est_BFP_GFP## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
#BFP expression depending of TET conc.
p_density_Tet.est_BFP_all_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Est")) %>%
#mutate(DOSE_1 = factor(DOSE_1,levels = c("0","100","500","1000"),ordered = TRUE)) %>%
ggplot(aes(log_BFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression -
Tetracyclin & Estradiol plasmids") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.est_BFP_all_plot 
BFP expression depending of Tet conc.
p_density_Tet.est_BFP_same_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Est")) %>%
#mutate(DOSE_1 = factor(DOSE_1,levels = c("0","100","500","1000"),ordered = TRUE)) %>%
ggplot(aes(log_BFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
#facet_wrap(vars(DOSE),nrow = 3) +
scale_color_viridis(name = "DOSE (µM),
Tet/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression -
Tetracyclin & Estradiol plasmids") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.est_BFP_same_plot 
LINCOLN BFP expression depending of
p_density_Tet.est_BFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Est")) %>%
ggplot(lincoln_weather, mapping = aes(x = log_BFP, y = DOSE, fill = stat(x))) +
geom_density_ridges_gradient(alpha = 0.1, adjust = 0.0001, scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Expression", option = "magma") +
theme_bw() +
ggtitle("Density plots for BFP expression -
Tetracyclin & Estradiol plasmids") +
ylab("DOSE (µM)") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))## Warning: Ignoring unknown parameters: adjustp_density_Tet.est_BFP_lincoln## Picking joint bandwidth of 0.0931
GFP
#GFP expression depending of EST conc.
p_density_Tet.est_GFP_all_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Est")) %>%
#mutate(DOSE_1 = factor(DOSE_1,levels = c("0","100","500","1000"),ordered = TRUE)) %>%
ggplot(aes(log_EGFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for GFP expression -
Tetracyclin & Estradiol plasmids") +
ylab("Density") +
xlab("GFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.est_GFP_all_plot 
GFP expression depending of EST conc.
p_density_Tet.est_GFP_same_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Est")) %>%
ggplot(aes(log_EGFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
scale_color_viridis(name = "DOSE (µM),
Tet/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for GFP expression -
Tetracyclin & Estradiol plasmids") +
ylab("Density") +
xlab("GFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.est_GFP_same_plot 
LINCOLN GFP expression depending of
p_density_Tet.est_GFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Est")) %>%
ggplot(lincoln_weather, mapping = aes(x = log_EGFP, y = DOSE, fill = stat(x))) +
geom_density_ridges_gradient(alpha = 0.1, adjust = 0.0001, scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Expression", option = "magma") +
theme_bw() +
ggtitle("Density plots for GFP expression -
Tetracyclin & Estradiol plasmids") +
ylab("DOSE (µM)") +
xlab("GFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))## Warning: Ignoring unknown parameters: adjustp_density_Tet.est_GFP_lincoln## Picking joint bandwidth of 0.0357
Double plasmid Tetracycline & Copper
#BFP & RFP violin expression
p_violin_Tet.cup_BFP_RFP =
tbl_tidy %>%
filter(STRAIN %in% c("Tet.Cup")) %>%
filter(NUM.IND %in% c("2")) %>%
filter(CHANNEL %in% c("log_BFP","log_miRFP670")) %>%
ggplot(aes(x = DOSE,y = INTENSITY,group = DOSE, fill = DOSE)) +
geom_violin(alpha = 0.5, adjust = 0.0001,draw_quantiles = 0.5) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
stat_compare_means(ref.group = "0/0",label = "p.signif", method = "wilcox.test") +
ggtitle("Violin plot of BFP & RFP intensity -
Tetracyclin & Copper plasmids") +
facet_wrap(vars(CHANNEL, STRAIN)) +
xlab("Tetracyclin and Copper (µM)") +
ylab("Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_violin_Tet.cup_BFP_RFP## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
#BFP expression depending of Tet conc.
p_density_Tet.cup_BFP_all_plots =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup")) %>%
ggplot(aes(log_BFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression -
Tetracyclin & Copper plasmids") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup_BFP_all_plots 
BFP expression depending of Tet conc.
p_density_Tet.cup_BFP_same_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup")) %>%
#mutate(DOSE_1 = factor(DOSE_1,levels = c("0","100","500","1000"),ordered = TRUE)) %>%
ggplot(aes(log_BFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
#facet_wrap(vars(DOSE),nrow = 3) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression -
Tetracyclin & Copper plasmids") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup_BFP_same_plot 
LINCOLN BFP expression depending of
p_density_Tet.cup_BFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup")) %>%
ggplot(lincoln_weather, mapping = aes(x = log_BFP, y = DOSE, fill = stat(x))) +
geom_density_ridges_gradient(alpha = 0.1, adjust = 0.0001, scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Expression", option = "magma") +
theme_bw() +
ggtitle("Density plots for BFP expression -
Tetracyclin & Copper plasmids") +
ylab("DOSE (µM)") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))## Warning: Ignoring unknown parameters: adjustp_density_Tet.cup_BFP_lincoln## Picking joint bandwidth of 0.0989
RFP
#RFP expression depending of CUP conc.
p_density_Tet.cup_RFP_all_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup")) %>%
ggplot(aes(log_miRFP670, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for RFP expression -
Tetracyclin & Copper plasmids") +
ylab("Density") +
xlab("RFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup_RFP_all_plot 
GFP expression depending of Tet conc.
p_density_Tet.cup_RFP_same_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup")) %>%
ggplot(aes(log_miRFP670, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for RFP expression -
Tetracyclin & Copper plasmids") +
ylab("Density") +
xlab("RFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup_RFP_same_plot 
LINCOLN GFP expression depending of
p_density_Tet.cup_RFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup")) %>%
ggplot(lincoln_weather, mapping = aes(x = log_miRFP670, y = DOSE, fill = stat(x))) +
geom_density_ridges_gradient(alpha = 0.1, adjust = 0.0001, scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Intesity (a.u.)", option = "magma") +
theme_bw() +
ggtitle("Density plots for RFP expression -
Tetracyclin & Copper plasmids") +
ylab("DOSE (µM)") +
xlab("RFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))## Warning: Ignoring unknown parameters: adjustp_density_Tet.cup_RFP_lincoln## Picking joint bandwidth of 0.0438
(p_density_Tet.cup_RFP_same_plot + p_density_Tet.cup_RFP_lincoln)/(p_density_Tet.cup_RFP_same_plot + p_density_Tet.cup_RFP_lincoln)## Picking joint bandwidth of 0.0438
## Picking joint bandwidth of 0.0438
p_density_Tet.cup_RFP_same_plot/p_density_Tet.cup_RFP_lincoln## Picking joint bandwidth of 0.0438
Three plasmids ########3
#BFP & RFP & GFP violin expression
p_violin_Tet.cup.est =
tbl_tidy %>%
filter(STRAIN %in% c("Tet.Cup.Est")) %>%
filter(NUM.IND %in% c("3")) %>%
filter(CHANNEL %in% c("log_BFP","log_EGFP", "log_miRFP670")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(aes(x = DOSE,y = INTENSITY,group = DOSE, fill = DOSE)) +
geom_violin(alpha = 0.5, adjust = 0.0001,draw_quantiles = 0.5) +
scale_color_viridis(name = "DOSE (µM), \nTet/Cup/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM), \nTet/Cup/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
stat_compare_means(ref.group = "0/0/0",label = "p.signif",method = "wilcox.test") +
ggtitle("Violin plot of BFP, GFP & RFP intensity - Tetracyclin & Copper plasmids") +
facet_wrap(vars(CHANNEL)) +
xlab("") +
ylab("Intesity (a.u.)") +
theme(aspect.ratio = 1,
plot.title = element_text(hjust = 0.5, face = "bold", size = 15),
axis.text.x = element_text(angle = 45,hjust = 1))
p_violin_Tet.cup.est## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_violin_Tet.cup.est.png")## Saving 12 x 5 in image## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' valuesBFP
#BFP expression depending of Tet conc.
p_density_Tet.cup.est_BFP_all_plots =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(aes(log_BFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1,
plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup.est_BFP_all_plots 
#BFP expression depending of Tet conc.
p_density_Tet.cup.est_BFP_same_plots =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(aes(log_BFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
#facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for BFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("Density") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup.est_BFP_same_plots 
LINCOLN BFP expression depending of
p_density_Tet.cup.est_BFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(lincoln_weather, mapping = aes(x = log_BFP, y = DOSE, fill = stat(x))) +
geom_density_ridges_gradient(alpha = 0.1, adjust = 0.0001, scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Intesity (a.u.)", option = "magma") +
theme_bw() +
ggtitle("Density plots for BFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("DOSE (µM)") +
xlab("BFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))## Warning: Ignoring unknown parameters: adjustp_density_Tet.cup.est_BFP_lincoln## Picking joint bandwidth of 0.0988
RFP
#RFP expression depending of CUP conc.
p_density_Tet.cup.est_RFP_all_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(aes(log_miRFP670, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for RFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("Density") +
xlab("RFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup.est_RFP_all_plot 
RFP expression depending of Tet conc.
p_density_Tet.cup.est_RFP_same_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(aes(log_miRFP670, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for RFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("Density") +
xlab("RFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup.est_RFP_same_plot 
LINCOLN RFP expression depending of
p_density_Tet.cup.est_RFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(lincoln_weather, mapping = aes(x = log_miRFP670, y = DOSE, fill = stat(x))) +
geom_density_ridges_gradient(alpha = 0.1, adjust = 0.0001, scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Intesity (a.u.)", option = "magma") +
theme_bw() +
ggtitle("Density plots for RFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("DOSE (µM)") +
xlab("RFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))## Warning: Ignoring unknown parameters: adjustp_density_Tet.cup.est_RFP_lincoln## Picking joint bandwidth of 0.0356
GFP
#GFP expression depending of EST conc.
p_density_Tet.cup.est_GFP_all_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(aes(log_EGFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
facet_wrap(vars(DOSE),nrow = 1) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for GFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("Density") +
xlab("GFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup.est_GFP_all_plot 
GFP expression depending of EST conc.
p_density_Tet.cup.est_GFP_same_plot =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(aes(log_EGFP, color = DOSE, fill = DOSE)) +
geom_density(alpha = 0.5, adjust = 0.0001) +
scale_color_viridis(name = "DOSE (µM),
Tet/Cup/Est",discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
scale_fill_viridis(name = "DOSE (µM),
Tet/Cup/Est", discrete = T,direction = -1, option = "A",begin = 0.2, end=0.8) +
theme_bw() +
ggtitle ("Density plots for GFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("Density") +
xlab("GFP Intesity (a.u.)") +
theme(aspect.ratio = 1,plot.title = element_text(hjust = 0.5, face = "bold", size = 15))
p_density_Tet.cup.est_GFP_same_plot 
LINCOLN GFP expression depending of
p_density_Tet.cup.est_GFP_lincoln =
tbl_red_green_blue %>%
filter(STRAIN == c("Tet.Cup.Est")) %>%
mutate(DOSE = factor(DOSE, levels = c("0/0/0", "0.5/500/0.005", "1/500/0.01"))) %>%
ggplot(lincoln_weather, mapping = aes(x = log_EGFP, y = DOSE, fill = stat(x))) +
geom_density_ridges_gradient(alpha = 0.1, adjust = 0.0001, scale = 3, rel_min_height = 0.01) +
scale_fill_viridis_c(name = "Intesity (a.u.)", option = "magma") +
theme_bw() +
ggtitle("Density plots for GFP expression -
Tetracyclin, Estradiol & Copper plasmids") +
ylab("DOSE (µM)") +
xlab("GFP Intesity (a.u.)") +
theme(aspect.ratio = 1, plot.title = element_text(hjust = 0.5,face = "bold", size = 15))## Warning: Ignoring unknown parameters: adjustp_density_Tet.cup.est_GFP_lincoln## Picking joint bandwidth of 0.0297
#Used for saving all of the plots to local computer! Need to be changed!
p_violoin_tet_BFP## Warning: Computation failed in `stat_compare_means()`:
## argument "x" is missing, with no default## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="violoin_tet_BFP.png")## Saving 7 x 5 in image## Warning: Computation failed in `stat_compare_means()`:
## argument "x" is missing, with no default
## Warning: collapsing to unique 'x' values
## Warning: collapsing to unique 'x' values
## Warning: collapsing to unique 'x' values
## Warning: collapsing to unique 'x' values
## Warning: collapsing to unique 'x' values
## Warning: collapsing to unique 'x' valuesp_density_tet_BFP_diff_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_tet_BFP_diff_plot.png")## Saving 7 x 5 in imagep_density_tet_BFP_same_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_tet_BFP_same_plot.png")## Saving 7 x 5 in imagep_density_tet_BFP_lincoln## Picking joint bandwidth of 0.0883
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_tet_BFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0883p_violin_Tet.est_BFP_GFP## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="violin_Tet.est_BFP_GFP.png")## Saving 7 x 5 in image## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' valuesp_density_Tet.est_BFP_all_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.est_BFP_all_plot.png")## Saving 7 x 5 in imagep_density_Tet.est_BFP_same_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.est_BFP_same_plot.png")## Saving 7 x 5 in imagep_density_Tet.est_BFP_lincoln## Picking joint bandwidth of 0.0931
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.est_BFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0931p_density_Tet.est_GFP_all_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.est_GFP_all_plot.png")## Saving 7 x 5 in imagep_density_Tet.est_GFP_same_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.est_GFP_same_plot.png")## Saving 7 x 5 in imagep_density_Tet.est_GFP_lincoln## Picking joint bandwidth of 0.0357
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.est_GFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0357p_violin_Tet.cup_BFP_RFP## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="violin_Tet.cup_BFP_RFP.png")## Saving 7 x 5 in image## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' valuesp_density_Tet.cup_BFP_all_plots
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup_BFP_all_plots.png")## Saving 7 x 5 in imagep_density_Tet.cup_BFP_same_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup_BFP_same_plot.png")## Saving 7 x 5 in imagep_density_Tet.cup_BFP_lincoln## Picking joint bandwidth of 0.0989
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup_BFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0989p_density_Tet.cup_RFP_all_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup_RFP_all_plot.png")## Saving 7 x 5 in imagep_density_Tet.cup_RFP_same_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup_RFP_same_plot.png")## Saving 7 x 5 in imagep_density_Tet.cup_RFP_lincoln## Picking joint bandwidth of 0.0438
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup_RFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0438p_violin_Tet.cup.est## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="violin_Tet.cup.est.png")## Saving 7 x 5 in image## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' values
## Warning in regularize.values(x, y, ties, missing(ties), na.rm = na.rm):
## collapsing to unique 'x' valuesp_density_Tet.cup.est_BFP_all_plots
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_BFP_all_plots.png")## Saving 7 x 5 in imagep_density_Tet.cup.est_BFP_same_plots
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_BFP_same_plots.png")## Saving 7 x 5 in imagep_density_Tet.cup.est_BFP_lincoln## Picking joint bandwidth of 0.0988
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_BFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0988p_density_Tet.cup.est_RFP_all_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_RFP_all_plot.png")## Saving 7 x 5 in imagep_density_Tet.cup.est_RFP_same_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_RFP_same_plot.png")## Saving 7 x 5 in imagep_density_Tet.cup.est_RFP_lincoln## Picking joint bandwidth of 0.0356
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_RFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0356p_density_Tet.cup.est_GFP_all_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_GFP_all_plot.png")## Saving 7 x 5 in imagep_density_Tet.cup.est_GFP_same_plot
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_GFP_same_plot.png")## Saving 7 x 5 in imagep_density_Tet.cup.est_GFP_lincoln## Picking joint bandwidth of 0.0297
ggsave(path ="/Users/Edwin/Google Drive/CHALMERS/iGEM/WetLAB/All_plots/",filename ="density_Tet.cup.est_GFP_lincoln.png")## Saving 7 x 5 in image## Picking joint bandwidth of 0.0297